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I built wordle for desktop but using my own GUI library!

Developing desktop GUIs in Python often involves frameworks that are either low-level or restrictive. To address this, I created PyUIKit, a open source project and a component-based Python GUI library built on top of CustomTkinter. Its…

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Developing desktop GUIs in Python often involves frameworks that are either low-level or restrictive. To address this, I created PyUIKit, a open source project and a component-based Python GUI library built on top of CustomTkinter. Its goal is to provide a web-like, simple syntax for building GUIs efficiently. I'm trying to actively update PyUIkit, even though its not polished its usable.



To test the library, I built a desktop Wordle clone, which helped identify current limitations and areas for improvement.









Watch the Full Walkthrough



If you wanna watch the full process of how I built it then watch this:














Overview



The desktop Wordle app includes:




  • Six attempts to guess a five-letter word

  • Random word selection from a list of 450+ words

  • Color-coded tiles for feedback: green ✅, yellow ⚠️, gray ❌

  • Toast notifications for user feedback



ScreenShot of wordle









PyUIKit GUIs



With PyUIKit, UI components are composed in a nested, web-like structure:




from pyuikit import Body, Div, Input
from pyuikit.components import Text, Button

app = Body(resizable=(False, False), height=600, width=800, title='Wordle')

Div(
height=600,
width=800,
bg_color='#121213',
children=[
Text(text="WORDLE", font_size=30, color="white"),
Div(horizontal=True, nested=True, children=[
Input(id='row1_col1', width=50, height=50, multiline=True),
Button(text="Submit", on_click=lambda: handlesubmit(1))
])
]
)

app.run()












Handling Wordle Logic






def handlesubmit(rownum):
letters = [Input.get_input_text(f'row{rownum}_col{i+1}') for i in range(5)]
# Two-pass check: green first, then yellow/gray
# Toast feedback if correct or attempt used












Limitations discovered




  • Single-line Input components cannot have custom heights

  • Font customization is limited

  • Dynamic background color updates are not fully supported









Future Improvements for PyUIKit




  • Easier, more concise update functions

  • Better Div layouts for flexible UI composition

  • Improved input handling, styling, and responsiveness









Conclusion



This Wordle project served as a practical stress test to identify PyUIKit’s current limitations and guide its evolution. While PyUIKit may not yet compete with more mature GUI frameworks, it is under active development, and projects like this play a crucial role in uncovering weaknesses, refining APIs, and shaping future improvements.



If you like the project please consider giving us a star on the github repo.



PyUIKit links:



1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
Syntax validiert (0 Fehler)
title: Detect Exploitation - I built wordle for desktop but using my own GUI library!
id: a4a0e591-c072-4523-88e6-7560e1501ff6
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "I built wordle for desktop but" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("I built wordle for desktop but using my ")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*I built wordle for desktop but using my *"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "I built wordle for desktop but using my "
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

2. Cyber Threat Intelligence & Forensik

🎯
MITRE ATT&CK Matrix Navigator 14 Taktiken
Reconnaissance
-
Resource Development
-
Initial Access
Execution
Persistence
-
Privilege Escalation
Defense Evasion
Credential Access
-
Discovery
-
Lateral Movement
-
Collection
-
Command and Control
Exfiltration
-
Impact
tsecurity.de Cognitive Threat RAG
Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich I built wordle for desktop but using my .... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

🛡️ Angriffsfläche & Exposure

Netzwerk/Remote-Zugriff ohne Vorauthentifizierung möglich.

⚡ Empfohlene Sofortmaßnahmen
  • 1. Perimeter-Inspektion: Relevante Portfreigaben und exponierte Endpunkte unverzüglich scannen.
  • 2. Patch-Applikation: Hersteller-Hotfix einspielen oder betroffene Daemons in isolierte DMZ-Segmente überführen.
  • 3. Telemetrie & EDR-Alerts: Prozessaufrufe und Child-Processes auf anomale Shell-Spawns überwachen.
🔗 Semantisch verwandte Zero-Days MariaDB 11.7 VEC
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